Clive Baldock
Clive Baldock
A full-scale attention-augmented CNN-transformer model for segmentation of oropharyngeal mucosa organs-at-risk in radiotherapy [0.03%]
一种用于放射治疗口咽黏膜器官风险区域分割的全规模注意力增强CNN-Transformer模型
Lian He,Jianda Sun,Shanfu Lu et al.
Lian He et al.
Radiation-induced oropharyngeal mucositis (ROM) is a common and severe side effect of radiotherapy in nasopharyngeal cancer patients, leading to significant clinical complications such as malnutrition, infections, and treatment interruption...
A comprehensive investigation of the radiation isocentre spatial variability in linear accelerators: implications for commissioning, QA, and clinical protocols [0.03%]
调强治疗放射线等中心位置变动的全面分析：对调试、质量保证及临床常规的启示
Zhen Hui Chen,Hans Lynggaard Riis,Rohen White et al.
Zhen Hui Chen et al.
Achieving greater accuracy in transcranial magnetic stimulation corticospinal evaluation and motor mapping by improving motor evoked potential recording: an emerging issue [0.03%]
通过改进运动诱发电位记录提高经颅磁刺激皮层脊髓评价和运动定位准确性的新问题
Marco Antonio Cavalcanti Garcia,Ana Carolina Borges Valente,Victor Hugo Moraes et al.
Marco Antonio Cavalcanti Garcia et al.
Clinical evaluation of motion robust reconstruction using deep learning in lung CT [0.03%]
基于深度学习的肺部CT运动鲁棒性重建临床评估
Shiho Kuwajima,Daisuke Oura
Shiho Kuwajima
In lung CT imaging, motion artifacts caused by cardiac motion and respiration are common. Recently, CLEAR Motion, a deep learning-based reconstruction method that applies motion correction technology, has been developed. This study aims to ...
Prop scan versus roll scan: selection for cranial three-dimensional rotational angiography using in-house phantom and Figure of Merit as parameter [0.03%]
基于参数Figure of Merit的颅内三维旋转DSA成像模体效果研究及临床评价
Ika Hariyati,Ani Sulistyani,Matthew Gregorius et al.
Ika Hariyati et al.
This study introduces a novel optimization framework for cranial three-dimensional rotational angiography (3DRA), combining the development of a brain equivalent in-house phantom with Figure of Merit (FOM) a quantitative evaluation method. ...
A review of image processing and analysis of computed tomography images using deep learning methods [0.03%]
基于深度学习的CT影像处理与分析研究综述
Darcie Anderson,Prabhakar Ramachandran,Jamie Trapp et al.
Darcie Anderson et al.
The use of machine learning has seen extraordinary growth since the development of deep learning techniques, notably the deep artificial neural network. Deep learning methodology excels in addressing complicated problems such as image class...
Evolutionary optimization-based descendent adaptive filter for noise confiscation in electrocardiogram signals [0.03%]
基于进化优化的后代自适应滤波器在心电图信号去噪中的应用
Shubham Yadav,Suman Kumar Saha,Rajib Kar et al.
Shubham Yadav et al.
Electrocardiogram (ECG) signals are usually contaminated by numerous artefacts during the recording process, and the quality of physiological information related to the heart is compromised. Due to this, artefact cancellation has become nec...
Measurement and application of the optimum value of head scatter correction factors in Radcalc for 6MV photon beams from varian linear accelerators [0.03%]
Varian直线加速器6MV光子束Radcalc最佳头部散射校正因子的测定与应用
Neil Richmond,Katie Chester,Craig Macdougall
Neil Richmond
To determine the optimum value of head scatter correction factor ([Formula: see text]) used in Radcalc software. The head scatter factors for a selection of multi-leaf collimator fields were measured on a Varian TrueBeam Edge and TrueBeam l...
Obsessive-compulsive disorder detection using ensemble of scalp EEG-based convolutional neural network [0.03%]
基于头皮EEG的卷积神经网络集成在强迫症检测中的应用研究
Faezeh Ghasemi,Ahmad Shalbaf,Ali Esteki
Faezeh Ghasemi
Obsessive-compulsive disorder (OCD) causes unwanted thoughts and repetitive actions and leads to many problems in a person's life. In this study, Electroencephalography (EEG) signals and deep learning methods were used to diagnose OCD patie...